Bibliographic record
Abstract
STUDY DESIGN: Technical report on harvesting method for human cadaveric cervical spine. OBJECTIVES: Description of a new method for harvesting the intact cervical spine during routine autopsies, including the atlanto-occipital and cervico-thoracic joints, without visible disfigurement above the suprasternal notch. SUMMARY OF BACKGROUND DATA: Despite the need for cervical spine specimens, there are only few articles describing procedures for harvesting an intact cervical spine. Presently available techniques either do not preserve the atlanto-occipital joint or leave visible disfigurement. METHODS: The body was placed in a prone position with the head flexed, and a posterior midline incision was performed. The spine was separated from surrounding tissue, then the caudal end was cut off through the Th1/Th2 disc space. A circular craniotomy provided access to the cranial base. A square window surrounding the foramen magnum was cut at the cranial base (through the sella turcica, the internal occipital protuberance, and 5 cm parasagittal on either side), and the entire cervical spine extracted through the posterior incision. The defect was reconstructed using wood and plaster materials. RESULTS: Eighteen specimens were harvested to date using this method. The average time of harvesting the cervical spine was less than 30 minutes. Reconstruction using wood and plaster resulted in a nearly normal appearance of the neck. CONCLUSIONS: Using this technique, the nuchal ligament providing stability to the cervical spine can be preserved. The suggested method was found simple, efficient, and reproducible for harvesting the intact cervical spine, including the atlanto-occipital and cervico-thoracic joints, from any routine autopsy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".